Search Results (550)

Electro-hydraulic servo pump-controlled systems have advantages such as energy saving and high integration and are widely applied in aerospace, engineering machinery, and other fields. However, the input and state delays introduced by drive circuit, control period, and oil leakage result in lower dynamic response speed compared to traditional valve control systems, which restricts the promotion of the system. In this paper, a prescribed performance trajectory tracking control method is proposed to improve the transient and steady-state performance of the system. A performance function is designed to constrain the range of trajectory tracking errors. The constrained space is mapped to an unconstrained space via a homeomorphic transformation, and the control laws are designed by integrating it with the backstepping method. In the final step of the backstepping design, the input and state delays are processed using Lyapunov–Krasovskii functionals. The simulation and experimental results show that under the condition of fixed input delay and state delay, the trajectory tracking errors converge within the preset range, and all states of the system are uniformly bounded. The results demonstrate the effectiveness of the proposed method in this paper. Full article

Self-powered sensors are critically important for IoT, yet most rely on synthetic polymers that lack environmental sustainability. This work presents a triboelectric nanogenerator (TENG) made from marine biowaste which operates as both an energy generator and humidity sensor. Abalone shell powder (ASP) majorly composed of calcium carbonate (CaCO₃) was used as its tribopositive layer in combination with polytetrafluoroethylene (PTFE) as tribonegative layer. The developed ASP-TENG device generated 410 V peak to peak open-circuit voltage (V_OC) and 2.79 W·m⁻² peak power density at an operating frequency of 4 Hz. These obtained results match or surpass existing biowaste-based TENGs. ASP-TENG efficiently worked as a self-powered humidity sensor because its output voltage decreased steadily from 410 V to 176 V in response to an increase in relative humidity (%RH) from 40% to 80% (decreases of 5.8 V for every 1%RH). The triboelectric charges become screened by water molecules that adsorb onto the porous CaCO₃ surface which leads to faster leakage current. This work demonstrates a sustainable method to create TENGs with multiple functions while developing environmentally friendly sensing systems for environmental tracking and sustainable energy harvesting. Full article

The well-balanced combination of high energy density and competitive cycle performance has established lithium-ion batteries as the technology of choice for Electric Vehicles (EVs) energy storage. Nevertheless, battery degradation continues to pose challenges to EV range, safety, and long-term reliability, making accurate estimation of their State of Health (SoH) crucial for efficient battery management, safety, and improved longevity. This paper addresses a compelling research question surrounding the possibility of developing a real-time, non-invasive, and efficient methodology for estimating lithium-ion battery SoH without battery removal, relying solely on voltage and current data. Our approach integrates the fitting abilities of Maximum Likelihood Estimation (MLE) with the dynamic uncertainty propagation of Bayesian Filtering to provide accurate and robust online SoH estimation. By reconstructing the open-circuit voltage curve from real-time data, the MLE estimates battery capacity during discharge cycles, while Bayesian Filtering refines these estimates, accounting for uncertainties and variations. The methodology is validated using an available dataset from Stanford University, demonstrating its effectiveness in tracking battery degradation under driving profiles. The results indicate that the approach can reliably estimate battery SoH with mean absolute errors below 1%, confirming its suitability for scalable EV applications. Full article

The increasing demand for reliable DC fast-charging stations in electric vehicle (EV) infrastructure necessitates efficient fault detection mechanisms to ensure operational stability and user safety. This paper will present the development of a diagnostic method for identifying open-circuit faults and short-circuit faults in DC charging stations by leveraging Total Harmonic Distortion (THD) analysis combined with a Second-Order Generalized Integrator (SOGI). The proposed approach uses the THD method to detect anomalies in the current and voltage waveforms, while the Frequency Locked Loop (FLL) serves to track the frequency of the grid and keep the SOGI tuned to it, and SOGI-FLL provides the rectifier with the capability of tracking the frequency, amplitude, voltage, and phase of the grid and monitoring these parameters of the grid. The ability to measure the THD is the kernel of the detection of faults. Detailed simulation confirms the method’s high sensitivity and robustness in detecting open/short circuit faults with minimal false positives. This technique offers a cost-effective, non-invasive diagnostic solution suitable for modern DC charging systems, contributing to improved reliability and efficiency of EV charging infrastructure. Full article

The influence of electron beam melting (EBM) scan speed on the corrosion, nano-biotribological, and cellular adhesion properties of Ti-6Al-4V-ELI (extra low interstitials) was systematically investigated. Specimens were fabricated using five different scanning speeds, and tribological performance was assessed via reciprocating dry wear tests, while corrosion behaviour was evaluated through monitoring the open circuit potential and anodic potentiodynamic polarization tests in Ringer’s solution. Human fibroblasts from the FN1 cell line were used to assess cell adhesion. Specimens produced using scanning speeds of 4530 mm·s⁻¹ and 4983 mm·s⁻¹ exhibited increased passive current densities, indicating reduced corrosion protection, although all surfaces maintained the passive film characteristic. Tribological behaviour was strongly dependent on scan speed, with wear rate and penetration depth increasing at higher speeds; notably, an intermediate scan speed produced a surface with minimal wear and penetration depth despite a wide wear track, suggesting enhanced resistance to tribological degradation. Fibroblast cultures demonstrated robust adhesion and spindle-shaped morphology across all samples, with the disk produced using a scanning speed of 4983 mm·s⁻¹ showing the highest surface coverage, highlighting the role of EBM process parameters in modulating surface properties relevant to cell–biomaterial interactions. These findings underscore the critical influence of scan speed on the multifunctional performance of Ti-6Al-4V-ELI for biomedical applications. Full article

To address the critical issue of low reliability caused by fault impacts in large-scale wind farms transmitting power over long distances via flexible DC transmission systems, this study proposes a collaborative solution. First, a new protection scheme integrating variable quantity differential protection, steady-state quantity differential protection and zero-sequence differential protection is proposed. By establishing a refined model of a wind farm with a flexible DC system, the adaptability of the differential protection for the outgoing lines is checked. Simulation results show that the sensitivity of metallic faults within the protection zone is better than 3.0, and the protection reliably remains inactive for faults outside the protection zone. Second, an innovative fault ride-through strategy combining self-regulating resistor circuits with wind farm MPPT load reduction is proposed. During faults on the receiving grid, the DC voltage fluctuation is controlled within 1.05 p.u. through graded switching of resistor modules and dynamic power regulation. This solution offers both rapid response and smooth fault ride-through characteristics, significantly improving the feasibility and economic viability of wind farm integration via flexible DC transmission. Full article

We developed a model to predict the quality of fresh goji berries during storage by analyzing the correlations of their dielectric properties. The variations in these properties with storage temperature, time, and frequency were systematically characterized to inform the model. Leveraging these relationships, we developed a model to predict quality. The analysis integrated measurements of dielectric properties with assessments of texture and key physicochemical indicators. Results indicate that dielectric parameters exhibit significant frequency dependence. Complex impedance (Z), capacitance (Cp), and resistance (Rp) all decreased sharply with increasing frequency, with the most pronounced change observed in Cp. Conductance, G, and reactance, X, increased with frequency, reaching maximum increases of 360.86% and 87.79%, respectively. Under the specific test frequency of 163,280 Hz, a strong polynomial relationship was observed between the dielectric parameters and storage time, with all fitted models yielding ${\mathit{R}}_{adj}^2$ values above 0.94. The quality factor Q (a dimensionless number for the energy efficiency of a resonant circuit or medium) showed a near-perfect correlation with brittleness, while reactance, X, was correlated with springiness and cohesiveness, with correlation coefficients approaching 0.999 under the optimal test frequency. The constructed ANN model demonstrated high prediction accuracy for hardness, brittleness, elasticity, cohesiveness, chewiness, and soluble solids content (R² > 0.97, MSE < 5%) but performed poorly in predicting adhesiveness, stickiness, and rebound elasticity (R² < 0.9). The constructed LSSVM model showed good prediction performance for some indicators (hardness, springiness, cohesiveness, and SSC) (R² > 0.94), but its prediction accuracy was low for brittleness and chewiness (R² < 0.9). Overall, its performance and generalization ability were inferior to the ANN model. This study shows that ANN models based on dielectric properties establish a technical foundation for the non-destructive, automated monitoring of goji berry storage quality, thereby providing a critical tool for dynamic quality tracking and value assessment within integrated warehouse management systems. Full article

To meet the safety and compliance requirements pertaining to robots when interacting physically with humans or the environment in unstructured settings such as households and factories, in this study, we focus on methods for the design and control of a flexible robotic magneto-rheological actuator (MRA). Firstly, for the magneto-rheological fluid clutch (MRC), which is the core component of the MRA, an equivalent magnetic circuit model was established to accurately calculate the magnetic field inside the clutch, and a thermal circuit model was constructed to analytically determine the operating temperature of each component. Considering practical engineering constraints, including mechanical structure, magnetic saturation, maximum current, and maximum temperature, a genetic algorithm was used to optimize parameters of the MRC. Secondly, based on the dynamic characteristics of the MRA, a dynamic model incorporating the motor, reducer, MRC, and load link was established. Given scenarios where torque sensors cannot be installed due to cost and structural space limitations, a model reference PID feedforward control strategy was designed. Torque was estimated using input current. Finally, an experimental platform was built, and static and dynamic torque output experiments were conducted. These experiments verified the excellent torque tracking performance of the designed MRA. Through multi-physics modeling, parameter optimization, and control strategy design, this paper provides a solution for flexible robotic joints that integrates high torque, high compliance, and safety. Full article

This paper presents a three-phase powerline energy harvesting circuit with doubly regulated output voltages to power wireless sensors for the monitoring of railroad powerline status. Three ring-shaped silicon steel cores coupled to the three phases of a powerline convert the line current into three-phase voltages, which are applied to an energy harvesting circuit. The key parts of the circuit are a series three-phase voltage rectifier, a buck–boost converter operating in discontinuous conduction mode (DCM), and a microcontroller unit (MCU) for maximum power point tracking (MPPT). The MCU performs two-step MPPT, coarse and fine, for impedance matching based on the perturb and observe method. Two parallel voltage regulators deliver 5 V and 5.7 V regulated DC voltages to power a radio and a set of sensors, respectively. The energy harvesting circuit is prototyped using commercial-off-the-shelf (COTS) components on an FR4 PCB. The measured maximum efficiency is 84% for the three-phase voltage rectifier and 89% for the buck–boost converter under the powerline current ranging from 5 A to 20 A. Full article

In the last few decades, several wearable devices have been designed to monitor respiration rate to capture pulmonary signals with a higher accuracy and reduce patients’ discomfort during use. In this article, we present the design and implementation of a device for the real-time monitoring of respiratory system movements. When breathing, the circumference of the abdomen and thorax changes; therefore, we used a Force-Sensing Resistor (FSR) attached to a Printed Circuit Board (PCB) to measure this variation as the patient inhales and exhales. The mechanical strain this causes changes the FSR electrical resistance accordingly. Also, for streaming this variable resistance on an Internet of Things (IoT) platform, Bluetooth Low Energy (BLE) 5 is utilized due to its adequate throughput, high accessibility, and the possibility of power consumption reduction. In addition to the sensing mechanism, the device includes a compact, energy-efficient micro-controller and a three-axis accelerometer that captures body movement. Power is supplied by a rechargeable Lithium-ion Polymer (LiPo) battery, and energy usage is optimized using a buck converter. For comfort and usability, the enclosure was 3D printed using Stereolithography (SLA) technology to ensure a smooth, ergonomic shape. This setup allows the device to operate reliably over long periods without disturbing the user. Altogether, the design supports continuous respiratory tracking in both clinical and home settings, offering a practical, low-power, and portable solution. Full article

This study deals with the fatigue behavior of on-site-installation-type track slabs subject to cycling train load developed by applying glass-fiber-reinforced polymer (GFRP) reinforcing bars. Concrete track slabs have the most severe deterioration in track circuit characteristic values due to the conduction influence of existing steel bars. Therefore, a track slab applying an insulator and lightweight GFRP reinforcement by replacing the existing steel bar was proposed from a design perspective. In order to present the validity of the proposed method, a full-size specimen was manufactured and a fatigue performance test was performed, and the results were compared with the test specimen applied with steel bars. From the results of various fatigue behaviors, it was found that displacement variations during cyclic loading remained within 1 mm, and load variations were within 10 kN, indicating excellent stability under accumulated fatigue cycles. This study analyzed the macro-level structural behavior of GFRP-reinforced concrete track slabs under fatigue loading. Future research will further investigate micro-level bond interactions between the reinforcement and concrete to validate long-term performance. Full article

The lithium-ion cell model is the heart of the battery management system—a more accurate model ensures operational safety, extends pack lifetime, and provides better tracking of battery charge and health. Catalyzed by the automotive industry’s shift towards electrification, optimal parameterization of the lithium-ion cell is of crucial importance. Two dominant methods of direct parameterization have emerged in the literature as the standard for parameter extraction of a lithium-ion equivalent circuit cell model. A direct comparison of their performance and suggestion as to the optimal method of cell parameterization has not yet been proposed; Thus, this paper aims to extract the optimal parameter set regarding the two dominant direct methods with an electrochemically based logic, compare the accuracy of cell parametrization over two transient load profiles, and ultimately suggest which method is preferable for electric vehicle applications. Additionally, this work will be conducted over multiple C-rates to quantify the robustness of each direct method of parameterization over a transient load profile. Full article

Quantum computing is an emergent field promising the improvement of processing speed in key algorithms by reducing their exponential scaling to polynomial, thus enabling solutions to problems that exceed classical computational capabilities. Gate-based quantum computing is the most common approach but still faces high levels of noise and decoherence. Gates play the role of probability mixers codifying information settled in quantum systems. However, they are deviated from their programmed behaviour due to those decoherent effects as a hidden source modifies the desired probability flux. Their quantification of such unavoidable behaviours becomes crucial for quantum error correction or mitigation. This work presents an approach to decoherence in quantum circuits using the Lindblad master equation to model the impact of noise and thermalisation underlying the ideal programmed behaviour expected for processing gates. The Lindblad approach then provides a comprehensive tool to model both probability fluxes being present in the process, thus regarding the gate and the environment. It analyses the deviation of resulting noisy states from the ideal unitary evolution of some gates considered as universal, setting some operating regimes. Thermalisation considers a radiation bath where gates are immersed as a feasible model of decoherence. Numerical simulations track the information loss as a function of the decay rate magnitude. It also exhibits the minimal impact on decoherence coming from particular quantum states being processed, but a higher impact on the number of qubits being processed by the gate. The methodology provides a unified framework to characterise the processing probability transport in quantum gates, including noise or thermalisation effects. Full article

A broad-temperature-range wavelength tracking system employing a thermistor monitoring circuit and a tunable optical filter is proposed and experimentally demonstrated. In this scheme, a thermistor monitoring circuit is utilized to acquire the real-time resistance values of a distributed feedback laser diode (DFB-LD). When the mapping relationship curve among thermistor resistance, temperature, and center wavelength of the DFB-LD is established, the drive voltage of the narrowband tunable optical filter is dynamically adjusted to regulate its filter window. Therefore, wavelength tracking is achieved by matching the filter window and the center wavelength of the DFB-LD. The experimental results show that the proposed system can achieve adaptive wavelength tracking within the operation band of 1539.4 nm to 1548.6 nm across a temperature range from −40 °C to 60 °C. The wavelength detection resolution and the minimum step of wavelength control are better than 0.79 pm and 0.1 nm, respectively. By exploiting the conversion characteristics between the thermistor and the center wavelength of the DFB-LD, this approach transforms laser wavelength detection into a low-cost, real-time electrical measurement, significantly enhancing transmission stability and reliability of laser sources in complex thermal environments. Full article

Wide-bandgap (WBG) perovskite solar cells (PSCs) are critical for high-efficiency tandem photovoltaic devices, but their practical application is severely limited by phase separation and poor film quality. To address these challenges, this study proposes a dual-additive passivation strategy using potassium thiocyanate (KSCN) and potassium chloride (KCl) to synergistically optimize the crystallinity and defect state of WBG perovskite films. The selection of KSCN/KCl is based on their complementary functionalities: K⁺ ions occupy lattice vacancies to suppress ion migration, Cl⁻ ions promote oriented crystal growth, and SCN⁻ ions passivate surface defects via Lewis acid-base interactions. A series of KSCN/KCl concentrations (relative to Pb) were tested, and the effects of dual additives on film properties and device performance were systematically characterized using scanning electron microscopy (SEM), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), photoluminescence (PL), space-charge-limited current (SCLC), current-voltage (J-V), and external quantum efficiency (EQE) measurements. Results show that the dual additives significantly enhance film crystallinity (average grain size increased by 27.0% vs. control), reduce surface roughness (from 86.50 nm to 24.06 nm), and passivate defects-suppressing non-radiative recombination and increasing electrical conductivity. For WBG PSCs, the champion device with KSCN (0.5 mol%) + KCl (1 mol%) exhibits a power conversion efficiency (PCE) of 16.85%, representing a 19.4% improvement over the control (14.11%), along with enhanced open-circuit voltage (Voc: +2.8%), short-circuit current density (Jsc: +6.7%), and fill factor (FF: +8.9%). Maximum power point (MPP) tracking confirms superior operational stability under illumination. This dual-inorganic-additive strategy provides a generalizable approach for the rational design of stable, high-efficiency WBG perovskite films. Full article